In order to improve the accuracy of sliding electric contact failure judgement of the pantograph-catenary, a multi-strategy fusion of improved northern goshawk optimisation algorithm (INGO) and least squares support vector machine (LSSVM) sliding electric contact failure diagnosis model is proposed. Firstly, the self-made sliding electric contact testing machine is used to carry out friction experiments, analyse the change rule of the current-carrying stability coefficient under different working conditions, and determine the criteria for the pantograph-catenary contact failure; secondly, the tent chaotic mapping, uniformly distributed dynamic adaptive weights, and the golden sinusoidal algorithm and the nonlinear convergence factor are used to improve the deficiencies in the NGO, and the simulation is carried out through the test function. Test, the results prove that the improved northern wing algorithm ( INGO) convergence speed and stability is better; finally, using the improved northern eagle optimisation algorithm on the model’ s parameter optimisation, to establish the sliding electrical contact failure diagnostic model. Comparing the proposed model with other diagnostic models, the diagnostic accuracy is improved by 16. 67%, 12. 5% and 8. 33% respectively, which further proves that the diagnostic model has high accuracy and generalisation ability.